1. Field of the Invention
The present invention relates to a technology for predicting, based on accumulation data in which a correlation between a combination of attribute values and a result of the combination is accumulated, a result of assessment target data including a new combination of the attribute values.
2. Description of the Related Art
In recent years, the research of a prediction system is progressing using a nonlinear analysis method such as a neural network and a support vector machine (SVM). The prediction system using these nonlinear analysis methods is also applicable to events having nonlinearity because the prediction system performs prediction based on learning unlike a prediction system using a conventional simple linear method.
There is a risk prediction system as an example of the prediction system to which the nonlinear analysis method is applied. The risk prediction system predicts risk of occurrence of disease from combinations of genes. There are an enormous number of combination patterns of genes, and there is a nonlinear effect represented by hierarchical genetic population structure. Therefore, an appropriate prediction result can be obtained by the prediction system using the nonlinear analysis method rather than the prediction system using the simple linear method.
Japanese Patent Application Laid-Open No. 2003-004739 discloses a technology of predicting risk of occurrence of disease from combinations of genes using the nonlinear analysis method.
The prediction system using the nonlinear analysis method, however, has a problem such that reliability of prediction is dependent on a process of learning because prediction accuracy is dependent on a learning sequence or the level of learning. Furthermore, the basis of prediction is quite vague, and it is, therefore, difficult to show the clear basis for a prediction result.
Because the prediction of disease risk is affected on life in some cases, it is very important to present the prediction result with high accuracy and clear basis.